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» Redundancy based feature selection for microarray data
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JIPS
2007
134views more  JIPS 2007»
14 years 9 months ago
An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology
: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...
IBPRIA
2009
Springer
15 years 1 months ago
Textural Features for Hyperspectral Pixel Classification
Hyperspectral remote sensing provides data in large amounts from a wide range of wavelengths in the spectrum and the possibility of distinguish subtle differences in the image. For...
Olga Rajadell, Pedro García-Sevilla, Filibe...
BMCBI
2010
115views more  BMCBI 2010»
14 years 9 months ago
Assessment and optimisation of normalisation methods for dual-colour antibody microarrays
Background: Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour a...
Martin Sill, Christoph Schroder, Jörg D. Hohe...
ICPR
2006
IEEE
15 years 10 months ago
Feature selection based on the training set manipulation
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Pavel Krízek, Josef Kittler, Václav ...
SSPR
1998
Springer
15 years 1 months ago
Regularization by Adding Redundant Features
The Pseudo Fisher Linear Discriminant (PFLD) based on a pseudo-inverse technique shows a peaking behaviour of the generalization error for training sample sizes that are about the...
Marina Skurichina, Robert P. W. Duin